PERSPECTIVES ON TEACHING
Although the challenges to getting students involved in the material vary across courses, several broader ideas guide my perspective on teaching. First, at the end of the semester, I want my students to leave class with something that stays with them — whether it’s what wealth inequality looks like today or what they should pay attention to when reading news articles that use statistics. Because much of what we teach is soon forgotten, I regularly include activities geared toward participation and material retention.
Second, as an instructor I aim to teach both content and skills in my courses. Along with a distinct worldview, sociology should equip students with strong research skills and the understanding that opinions must be well informed and supported by evidence. These skills are incredibly valuable in a world full of misinformation, where ideology often trumps research. Thus, my goal is to provide students with a better understanding of the social world, along with practical knowledge that will help them navigate it.
UNIVERSITY OF ALBERTA COURSES
SOC 260: Inequality and Social Stratification
Stratification refers to systematic social inequality in the access of opportunities, resources, and rewards. It involves the uneven distribution of people across social categories based upon achieved and ascribed characteristics. Human societies differ greatly in the extent of stratification present within them. This course focuses on social stratification in Canada and the United States with some comparisons to other industrialized countries. We will address how stratification has varied throughout history and question why members of certain groups advance while others do not.
The course is divided into two primary parts. Part I describes the processes and theories behind stratification. During this part of the course we will discuss the social construction of categories, the mechanisms behind the unequal distribution of rewards, and explanations for varying levels of stratification. Part II investigates multiple bases of stratification, such as race/ethnicity, gender, age, and class, along with different areas of stratification, including credit markets, work, health, consumption, and education.
SOC 210: Introduction to Social Statistics
Statistics are everywhere in our data driven world. Statistics permeate media news coverage and apply to all areas of life, from finance to shopping to sports. Statistical techniques also play a prominent role across a variety of occupations that include research, marketing, data management, and public policy jobs. Mastering basic statistical concepts and techniques therefore will improve your understanding of the social world, better equip you to enter various professions, and help you to make important life decisions.
SOC 210 provides an introduction to statistical concepts and methods used by social scientists to analyze quantitative data. The course is divided into three parts. Part I covers descriptive statistics. During this part of the course we will learn about frequency distributions, measures of central tendency, and the normal curve. We will also address where data come from, along with data visualization. Part II focuses on inferential statistics. In Part II we will focus on probability and sampling, estimation procedures, hypothesis testing, and bivariate tables. Part III incorporates measures of association. During this part of the course we will cover bivariate measures of association, along with bivariate and multivariate regression.
SOC 402/456: Data Analysis and Research
This course provides a hands-on introduction to data analysis for social science research with a focus on examples from sociology. It is designed to provide students with the necessary skills to analyze data, interpret results, and conduct research. This course covers topics that include the logic of scientific inquiry, introductory statistics, and common research techniques used in the social sciences. Students will gain experience with the practical side of statistics and research by learning to explore, analyze, interpret, and present data – tasks that permeate the social sciences and many other fields. Students will also have the opportunity to translate their general interests into a well-defined research topic, analyze data related to that topic, and communicate findings to a general audience. With a focus on developing research, writing, and presentation skills, the course provides instruction on how to use Excel and R to summarize and analyze data, opportunities to evaluate research and writing, and information on how best to share study findings with different audiences.
SOC 672: Social Structure and Public Policy
This course addresses the intersection of three interconnected areas in sociology: stratification, social structure, and public policy. Knowledge of stratification is integral to an understanding of social structure and policy. The concept of stratification, which refers to structural inequality in the access of opportunities, resources, and rewards, lies at the heart of many debates about social structure. Structure is in its very definition. Policy then acts a means to influence stratification. Through public policy, governments and other institutions directly and indirectly affect the broader social structure.
This course is divided into three parts. Part I focuses on stratification and social structure. In this part of the course we will look at foundations and mechanisms behind stratification and the role of social structure in determining outcomes. Part II focuses on public policy. In this part of the course we will discuss social policy and the welfare state, along with specific policies related to taxation and redistribution. Part III builds on the theories presented in Part I and the broad policies discussed in Part II to address stratification and social policy across different areas of society that include labor and credit markets, immigration, health, and the criminal justice system.
R for Social Statistics Workshop
This one-day workshop provides a friendly introduction to the statistical data analysis program, R. We cover the basic structure and functions of R; data entry and management in R; and ways to describe, visualize, and analyze data in R. Please note that the course is intended for persons with some statistical background. Registrants should have a working knowledge of hypothesis testing, correlation, and regression, as these topics will be included in the workshop.
R (cran.r-project.org) is a free computing language and software environment that provides access to a variety of statistical and graphic techniques. Due to its open source structure and flexibility, R has been growing in popularity since its official release in 2000, making it one of the most widely used statistical software programs both inside and outside academia. Although many software programs and coding languages for data analysis exist, R is one of the few software environments directly oriented towards statistical analyses, which is continually expanding through the implementation of user-created packages. In addition, a large active community of programmers, statisticians, and researchers continue to strengthen the program and the resources available.
Please see the Sociology Department’s website for the most up-to-date syllabi: Course Outlines